Technical Field
The present technique relates to the field of data processing. More particularly, the present technique relates to an apparatus and method for performing a floating-point square root operation.
Technical Background
In floating-point representation, numbers are represented using a mantissa (also known as a significand) 1.F or 0.F, an exponent E and a sign bit S. The sign bit represents whether the floating-point number is positive or negative, the mantissa represents the significant digits of the floating-point number, and the exponent represents the position of the radix point (also known as a binary point) relative to the mantissa. By varying the value of the exponent, the radix point can “float” left and right within the mantissa. This means that for a predetermined number of bits, a floating-point representation can represent a wider range of numbers than a fixed point representation (in which the radix point has a fixed location within the mantissa). However, the extra range is achieved at the expense of reduced precision since some of the bits are used to store the exponent.
One example of a floating-point arithmetic operation is a floating-point square root operation which takes a radicand value having a radicand exponent and a radicand mantissa and determines a square root of either the radicand value or the reciprocal of the radicand value, to generate a result value having a result exponent and a result mantissa. The present technique seeks to improve processing performance for this type of operation.